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» Discovering Frequent Closed Itemsets for Association Rules
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CIKM
2004
Springer
14 years 1 months ago
Discovering frequently changing structures from historical structural deltas of unordered XML
Recently, a large amount of work has been done in XML data mining. However, we observed that most of the existing works focus on the snapshot XML data, while XML data is dynamic i...
Qiankun Zhao, Sourav S. Bhowmick, Mukesh K. Mohani...
APIN
2006
168views more  APIN 2006»
13 years 7 months ago
Utilizing Genetic Algorithms to Optimize Membership Functions for Fuzzy Weighted Association Rules Mining
It is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for fuzzy association rules mining. In general, it is unre...
Mehmet Kaya, Reda Alhajj
COMPSAC
2005
IEEE
13 years 9 months ago
A Novel Method for Protecting Sensitive Knowledge in Association Rules Mining
Discovering frequent patterns from huge amounts of data is one of the most studied problems in data mining. However, some sensitive patterns with security policies may cause a thr...
En Tzu Wang, Guanling Lee, Yu Tzu Lin
SPAA
1997
ACM
13 years 12 months ago
A Localized Algorithm for Parallel Association Mining
Discovery of association rules is an important database mining problem. Mining for association rules involves extracting patterns from large databases and inferring useful rules f...
Mohammed Javeed Zaki, Srinivasan Parthasarathy, We...
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
14 years 8 months ago
Real world performance of association rule algorithms
This study compares five well-known association rule algorithms using three real-world datasets and an artificial dataset. The experimental results confirm the performance improve...
Zijian Zheng, Ron Kohavi, Llew Mason